Systems | Development | Analytics | API | Testing

Distributed tracing is essential for managing the complexity of modern microservices. It provides visibility into how requests flow through interconnected systems, helping to identify bottlenecks, errors, and latency issues. As microservices adoption grows - 61% of enterprises already use them - tools like OpenTelemetry, Dynatrace, and DreamFactory are shaping the future of observability. Each offers unique solutions for monitoring and troubleshooting distributed systems.

SAP data scrambling is critical to protect business data. Over 90% of Fortune 500 companies manage their business operations using SAP systems. Each company typically maintains many non-production environments containing sensitive data. But when it comes to protecting SAP data, too many enterprise leaders believe the myths. To truly protect SAP data at your enterprise, you need to learn the truth and you need to adopt best practices. In this blog, we’ll share exactly that.

Outsourcing quality assurance (QA) used to be about saving money. In 2025, you will have to build resilience into the release pipeline.

In our recent webinar, we tackled a familiar frustration for many engineering teams: long build times. Our expert panel broke down the problem and explored how remote build caching can deliver faster builds, improved workflows, and real business value. Here are the five biggest takeaways.

Welcome back to our ongoing series on strategies for gaining an unfair advantage. So far, we’ve explored how leveraging the tech ecosystem, overcoming adversity, unlocking hidden value in data, fostering great partnerships, and balancing risk with reward can set your organization apart. Each topic has offered actionable insights and real-world examples to help you stay ahead.

Sometimes the biggest opportunities come disguised as unproven protocols released on a random Monday. Here’s why we bet on MCP before anyone asked us to. ‍ Two months before anyone knew what MCP was, we made a bet that it would fundamentally transform how people interact with their data infrastructure.

When we first started using Playwright for automated testing, the built-in test runner and test reports seemed fine. It showed passed tests and failures, which worked for small projects. But as our large test suites and CI/CD pipelines expanded, the default test runner reports became limiting especially when analyzing detailed results from each test run, the default test runner reports became limiting—especially when analyzing large-scale test results.

AI Needs All Your Data. Your ETL Vendor Is Charging You to Keep It Locked Away. In this post, we explore why legacy ETL pricing models are fundamentally misaligned with the demands of modern AI workloads.